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# Synaptic Reconstruction | ||
# SynapseNet: Deep Learning for Automatic Synapse Reconstruction | ||
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Reconstruction of synaptic structures in electron microscopy. | ||
SynapseNet is a tool for segmentation and analysis of synapses in electron microscopy. | ||
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THIS IS WORK IN PROGRESS! | ||
To learn how to use SynapseNet, check out [the documentation](https://computational-cell-analytics.github.io/synapse-net/). | ||
To learn more about how it works, check out [our preprint](TODO). | ||
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## Installation | ||
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- Make sure conda or mamba is installed. | ||
- If you don't have a conda installation yet we recommend [micromamba](https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html) | ||
- Create the environment with all required dependencies: `mamba env create -f environment.yaml` | ||
- Activate the environment: `mamba activate synaptic-reconstruction` | ||
- Install the package: `pip install -e .` | ||
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## Tools | ||
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### Segmentation Correction | ||
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https://napari.org/stable/howtos/layers/labels.html | ||
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### Distance Measurements | ||
See an example reconstruction of a mossy fibre synapse with SynapseNet. | ||
Automatic segmentation of synaptic vesicles are rendered in orange, active zones in blue and two mitochondria in red and cyan. | ||
![Reconstruction of a mossy fiber synapse](doc/images/synapse-reconstruction.png) |
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